Data dependency mitigation in parallel decoders for flash storage

ABSTRACT

A memory device can include a memory array, a processor coupled to the memory array, and a decoding apparatus. The decoding apparatus is configured to perform parallel decoding of codewords. Each of the codewords has a plurality of data blocks, each data block having a number of data bits. The decoding apparatus is configured to decode in parallel two or more codewords, which share a common data block, to determine error information associated with each codeword. For each error, the error information identifies a data block having the and associated error bit patterns. The decoding apparatus is configured to update the two or more codewords based on the identified data blocks having errors and the associated error bit patterns.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims priority to U.S. Provisional ApplicationNo. 62/354,002, entitled “An Improved Data Dependency Mitigation SchemeFor Generalized Product Codes,” Attorney Docket No.098645-1015651-SK031-P, filed Jun. 23, 2016, commonly assigned andexpressly incorporated by reference herein in its entirety.

This application is also a continuation-in-part application of U.S.patent application Ser. No. 15/411,773, entitled “Data DependencyMitigation In Decoder Architecture For Generalized Product Codes,”Attorney Docket No. 098645-0971646-SK011-N, filed Jan. 20, 2017, whichclaims priority to U.S. Provisional Application No. 62/290,749, entitled“Data Dependency Mitigation In Decoder Architecture For GeneralizedProduct Codes,” Attorney Docket No. 098645-0971645-SK011-P, filed Feb.3, 2016, and U.S. Provisional Application No. 62/354,002, entitled “AnImproved Data Dependency Mitigation Scheme For Generalized ProductCodes,” Attorney Docket No. 098645-1015651-SK031-P, filed Jun. 23, 2016,all of which are commonly assigned and expressly incorporated byreference herein in their entirety.

This application is also related to U.S. patent application Ser. No.15/158,425 entitled “Generalized Product Codes For NAND Flash Storage,”filed May 18, 2016, which is commonly assigned and expresslyincorporated by reference herein in its entirety.

BACKGROUND

The term “error correcting code (ECC)” is used herein to refer to aprocess of adding redundant data, or parity data, to a message, suchthat it can be recovered by a receiver even when a number of errors wereintroduced, either during the process of transmission, or storage. Ingeneral, the ECC can correct the errors up to the capability of the codebeing used. Error-correcting codes are frequently used incommunications, as well as for reliable storage in media such as CDs,DVDs, hard disks, and random access memories (RAMs), flash memories,solid state disk (SSD), and the like.

In NAND flash storage enterprise applications, high read throughput is arelevant feature. Read latency can be reduced significantly if the ECCdecoder is able to decode the data using a single read from the NANDmedia (hard decoding). This motivated the ECC researchers to improveperformance for the hard decoding. With recent research findings forproduct codes, it has been confirmed that this class of codes providesbetter decoding performance compared to Bose-Chaudhuri-Hocquenghem (BCH)and low density parity check (LDPC) codes with a low complexityencoder/decoder when a single NAND read operation is performed.

A class of improved product codes has been proposed, as described inU.S. patent application Ser. No. 15/158,425 entitled “GeneralizedProduct Codes For NAND Flash Storage,” filed May 18, 2016, which iscommonly assigned and expressly incorporated by reference herein in itsentirety. This class of improved product codes, referred to asgeneralized product codes (GPC), has been shown to provide improvedperformance, for example, lower error floor.

BRIEF SUMMARY OF THE DISCLOSURE

Product codes can have structures in which two codewords can share acommon data block. For example, GPCs have a structure such that everypair of constituent codewords shares a certain number of data bits amongeach other (referred to as intersection of these codewords). If twodecoders are operated in parallel to decode a pair of constituentcodewords that share data bits, each decoder may try to correct bits inits intersection. This causes a clash in updating the errors in databits, and the hardware implementation of this decoder may behave in anunpredictable manner. This data dependency among constituent codes isalso problematic when single-constituent-decoder architecture withseveral pipeline stages is used. Moreover, this problem becomes severewhen the number of component decoders that run in parallel is increased.

In embodiments of this disclosure, a decoder is configured to decodemultiple constituent codewords in parallel to meet the desiredthroughput. The proposed decoder architecture mitigates the datadependency issue with minimal loss in the throughput compared with anupper bound obtained using an idealized hypothetical decoder. Thedecoder can be applied to any parallel decoding of constituent codewordsthat share at least one common data block, such as the parallel decodingof two constituent codewords from a GPC codeword or the paralleldecoding of a row codeword and a column codeword from a TPC codeword.Further, the term “parallel decoding” refers to some overlap in thedecoding time between two codewords. For example, the decoding of thefirst codeword can (or typically does) start before the decoding of thesecond codeword (and can end before it too).

According to some embodiments of the present disclosure, a memory deviceincludes a memory array, a processor coupled to the memory array, and adecoding apparatus. The decoding apparatus is configured to performcoarse decoding and fine decoding. In some embodiments, the finedecoding is performed only if it is determined that coarse decoding hasfailed to decode the codewords successfully. In coarse decoding, thedecoder decodes in parallel two or more codewords, which share a commonblock of bits, to determine error information. Next, the decodercorrects errors in a first codeword based on the error information.Then, it is determined if the shared common block of data bits iscorrected. If the shared common data block is updated, then errorcorrection based on the error information is prohibited in codewordssharing the common block of data bits with the first codeword. In finedecoding, a single codeword is decoded at a time for error correction.

According to some embodiments of the present disclosure, a decodingapparatus is configured for decoding a plurality of codewords inparallel. The apparatus includes a memory and a processor coupled to thememory. The processor is configured to read encoded data including aplurality of codewords, which is encoded in a product code in which eachcodeword has multiple blocks of data bits and every two codewords sharea common block with each other. One or more decoders are configured toperform parallel decoding of two or more codewords. The apparatus isconfigured to perform coarse decoding and fine decoding. In someembodiments, the fine decoding is performed only if it is determinedthat coarse decoding has failed to decode the codewords successfully. Inthe coarse decoding, the apparatus is configured to perform paralleldecoding of two or more codewords to determine error information, andupdate a first codeword if the error information indicates that an errorexists. The apparatus also determines if the common block between thefirst and second codewords is updated, and updates the second codewordbased on the error information, unless the common block is updated inthe decoding of the first codeword. In the fine decoding, the codewordsare decoded one at a time.

According to some embodiments of the present disclosure, a method fordecoding data includes reading, from a memory device, encoded dataincluding a plurality of codewords. The method includes decoding inparallel two or more codewords that share a common block of data bits,to determine error information, and correcting errors in a firstcodeword based on the error information. The method also determines ifthe shared common block of data bits is corrected, and, if sodetermined, prevents error correction based on the error information incodewords sharing a common block of data bits with the first codeword.The method can also include decoding a single codeword at a time forerror correction.

According to some embodiments of the present disclosure, a decodingapparatus configured for decoding a plurality of codewords in parallelcan include a memory, a processor coupled to the memory, and one or moredecoders configured to perform parallel decoding of two codewords. Theprocessor is configured to read encoded data including a plurality ofcodewords from the memory. The plurality of codewords is encoded in aproduct code in which each codeword has multiple data blocks, and eachdata block has a number of data bits.

In some embodiments, the apparatus is configured to perform paralleldecoding of first and second codewords sharing a common data block todetermine error information associated with each codeword. In theparallel decoding of two codewords, the decoding of each codeword atleast partially overlaps in time with the decoding of the othercodeword. For every error, the error information identifies the datablocks having the error and associated error bit pattern. The decodingapparatus is configured to update the first codeword based on the errorinformation indicating an error. If the error information indicates anerror in the decoding of the second codeword, the decoding apparatus isconfigured to determine whether to update the second codeword asfollows. First, the decoding apparatus determines if the common datablock between the first codeword and the second codeword has beenidentified as having an error in the decoding of the first codeword.Upon determining that the common data block has not been identified ashaving an error, the decoding apparatus updates the second codewordbased on the error information. Upon determining that the common datablock has been identified as having an error and that an error bitpattern in the common data block identified in the decoding of thesecond codeword is the same as an error bit pattern in the common datablock identified from the error information based on the decoding of thefirst codeword, the decoding apparatus updates data blocks other thanthe common data block in the second codeword without updating the commondata block. Further, upon determining that the common data block hasbeen identified as having an error and that the error bit pattern in thecommon data block identified in the decoding of the second codeword isdifferent from the error bit pattern in the common data block identifiedfrom the error information based on the decoding of the first codeword,skip the updating of the second codeword. In the latter case, the errorin the second codeword is not updated, and it can be processed in thenext decoding step.

According to some embodiments of the present disclosure, a method fordecoding data includes reading, from a memory, encoded data including aplurality of codewords. Each codeword has multiple data blocks and eachdata block includes a number of data bits. The method also includesdecoding, in parallel, a first codewords and second codeword that sharea common data block to determine error information associated with eachcodeword. In the parallel decoding of the first and second codewords,the decoding of the first codeword at least partially overlaps in timewith the decoding of the second codeword. For each error, the errorinformation identifies one or more data blocks having errors andassociated error bit patterns. The method further includes updating thecodewords based on the error information associated with the common datablock.

According to some embodiments of the present disclosure, a memory devicecan include a memory array, a processor coupled to the memory array, anda decoding apparatus. The decoding apparatus is configured to performparallel decoding of codewords. Each of the codewords has a plurality ofdata blocks, and each data block has a number of data bits. The decodingapparatus is configured to decode in parallel two or more codewords,which share at least a common data block, to determine error informationassociated with each codeword. For each error, the error informationidentifies a data blocks having the error and associated error bitpattern. The decoding apparatus is configured to update the two or morecodewords based on the identified one or more data blocks having errorsand the associated error bit patterns.

BRIEF DESCRIPTION OF THE DRAWINGS

An understanding of the nature and advantages of various embodiments maybe realized by reference to the following figures. In the appendedfigures, similar components or features may have the same referencelabel. Further, various components of the same type may be distinguishedby following the reference label by a dash and a second label thatdistinguishes among the similar components. If only the first referencelabel is used in the specification, the description is applicable to anyone of the similar components having the same first reference labelirrespective of the second reference label.

FIG. 1A is a simplified block diagram illustrating a data communicationsystem in accordance with certain embodiments of the present disclosure;

FIG. 1B is a simplified block diagram illustrating a conventionalproduct code;

FIG. 2A is a simplified block diagram illustrating a generalized productcode (GPC) in accordance with certain embodiments of the presentdisclosure;

FIG. 2B is a simplified block diagram illustrating an exemplaryconstruction of a generalized product code (GPC) in accordance withcertain embodiments of the present disclosure;

FIGS. 2C-2G are simplified block diagrams illustrating error correctionexamples in a generalized product code (GPC) in accordance with certainembodiments of the present disclosure;

FIG. 2H is a simplified block diagram illustrating another generalizedproduct code (GPC) in accordance with certain embodiments of the presentdisclosure;

FIG. 3A is a simplified block diagram illustrating an example of aBose-Chaudhuri-Hocquenghem (BCH) decoder in accordance with certainembodiments of the present disclosure;

FIG. 3B is a block diagram illustrating a decoder in accordance withcertain embodiments of the present disclosure;

FIG. 4 is a simplified block diagram illustrating two pipelined decodersdecoding six codewords in parallel in accordance with certainembodiments of the present disclosure;

FIG. 5 is a simplified block diagram illustrating a memory device, suchas a flash storage in accordance with certain embodiments of the presentdisclosure;

FIG. 6 is a simplified flow chart illustrating the operation of decodingapparatus 500 in accordance with certain embodiments of the presentdisclosure;

FIG. 7 is a simplified flow chart illustrating a coarse decodingoperation in accordance with certain embodiments of the presentdisclosure;

FIG. 8 is a simplified flow chart illustrating a fine decoding operation800 in accordance with certain embodiments of the present disclosure;

FIG. 9 is a simplified flow chart illustrating a method 900 for paralleldecoding in accordance with certain embodiments of the presentdisclosure;

FIG. 10 is a simplified flow chart illustrating another method forparallel decoding in accordance with alternative embodiments of thepresent disclosure;

FIG. 11 is a simplified block diagram illustrating an apparatus that maybe used to implement various embodiments according to the presentdisclosure.

DETAILED DESCRIPTION

FIG. 1A a simplified block diagram illustrating a data communicationsystem 100 in accordance with certain embodiments of the presentdisclosure. In the example shown, encoder 110 receives information bitsthat include data which is desired to be stored in a storage system 120or transmitted in a communications channel. The encoded data is outputby encoder 110 and is written to storage 120. In various embodiments,storage 120 may include a variety of storage types or media such as(e.g., magnetic) disk drive storage, Flash storage, etc. In someembodiments, the techniques described herein are employed in atransceiver and instead of being written to or read from storage, thedata is transmitted and received over a wired and/or wireless channel.In this case, the errors in the received codeword may be introducedduring transmission of the codeword.

When the stored data is requested or otherwise desired (e.g., by anapplication or user which stored the data), detector 130 receives thedata from the storage system. The received data may include some noiseor errors. Detector 130 performs detection on the received data andoutputs decision and/or reliability information corresponding to one ormore bits in a codeword. For example, a soft-output detector outputsreliability information and a decision for each detected bit. On theother hand, a hard output detector outputs a decision on each bitwithout providing corresponding reliability information. As an example,a hard output detector may output a decision that a particular bit is a“1” or a “0” without indicating how certain or sure the detector is inthat decision. In contrast, a soft output detector outputs a decisionand reliability information associated with the decision. In general, areliability value indicates how certain the detector is in a givendecision. In one example, a soft output detector outputs alog-likelihood ratio (LLR) where the sign indicates the decision (e.g.,a positive value corresponds to a “1” decision and a negative valuecorresponds to a “0” decision) and the magnitude indicates how sure orcertain the detector is in that decision (e.g., a large magnitudeindicates a high reliability or certainty).

The decision and/or reliability information is passed to decoder 140which performs decoding using the decision and reliability information.A soft input decoder utilizes both the decision and the reliabilityinformation to decode the codeword. A hard decoder utilizes only thedecision values in the decoder to decode the codeword. After decoding,the decoded bits generated by the decoder are passed to the appropriateentity (e.g., the user or application which requested it). With properencoding and decoding, the information bits match the decoded bits.

FIG. 1B a simplified block diagram illustrating a conventional productcode. FIG. 1B illustrates a two-dimensional turbo product code (TPC)codeword 150. As illustrated, the TPC codeword 150 may be a matrix ofsize (N+P_(c))×(M+P_(r)), in which N represents the number of rows ofinformation bits, M represents the number of columns of informationbits, P_(r) represents the number of row parity bits and P_(c)represents the number of column parity bits. Information bits can berepresented by a matrix of size N×M (e.g., matrix 160), row parity bitscan be represented by a matrix of size N×P_(r) (e.g., matrix 170), andColumn parity bits may be represented by a matrix of size P_(c)×M (e.g.,matrix 180). The TPC codeword may include N row codewords and M columncodewords. Each row codeword 190 includes multiple information bits 192and one or more parity bits 194. Similarly, each column codewordincludes multiple information bits and one or more parity bits. As anexample, if row constituent code is a BCH code, the row codewords 1through N are constructed using BCH encoding. Similarly, columncodewords 1 through M are generated using an error correctingconstituent code (e.g., BCH code, Reed Solomon code, etc.).

As an example, if the row constituent code has a code rate of 0.9, therow codeword may include 90 information bits and 10 parity bits. Ingeneral, row codewords and column codewords may have any code rate,without departing from the teachings of the present disclosure. Toobtain the row and column parity bits, a TPC encoder (not shown) firstencodes the N rows of information bits (shown as shaded blocks) togenerate the N row parity bit groups. Then, the TPC encoder encodes theM columns of information bits to generate the M column parity bit sets.

FIGS. 2A-2H are simplified schematic diagrams illustrating a generalizedproduct code (GPC) in accordance with certain embodiments of the presentdisclosure. As an example, a GPC is a product code in which informationbits are grouped in blocks, the blocks of information bits and one ormore XOR parity blocks arranged in a rectangular matrix of data blocks.In the example of FIG. 2A, the data blocks of information bits, alsoreferred to as information blocks, are numbered D1-D9, and each block Dkcontains I bits, where I is a positive integer. Each row of data ispermuted and the codeword parity is constructed on the permuted data,which is shown as Row Parity in FIG. 2A. In addition, the parities onthe parity (POP) are constructed by combining row parities column-wise.The arrangement is configured to remove miscorrections because the samecodeword will not be formed for different rows with changing datalocations with permutations. All the data blocks are protected twice;however, the row parity is protected once. The parity on parity (POP)will add another level of protection to remove errors in parities.

In FIG. 2B, a specific example is shown to explain the construction of aGPC. However, the method described here can be used for any class ofgeneralized product codes. For example, in other embodiments, theproduct code construction can be extended to higher dimensions. In anembodiment, data blocks can be protected three times in athree-dimensional generalized product code. In FIG. 2B, the number ofdata bits in a block, I, is taken as an integer, for example, from 8 to16, but it can be any chosen value depending upon desired data lengthand code rate. Let Ncw be the number of row codewords, which is equal tofive in FIG. 2B, i.e., there are five codewords designated as CW1-CW5.The block designated as “XOR” or “XOR parity” is constructed by takingXOR (exclusive OR) of all data blocks of length I, and the parities ofthe first (Ncw−1) row codewords. In some embodiments, multiple XORblocks can be formed, with each XOR block constructed based on a subsetof all data blocks of information bits. The length of the “XOR parity”block is also equal to I. All row parities are further encoded byanother constituent code which is called parity on parity or POP. Inthis code construction, the decoding criterion is such that the data isdecoded successfully if all Ncw codewords are decodable and XOR paritycheck is satisfied. This decoding criterion helps in avoidingmiscorrections which can make a valid codeword in a regular TPC decodingcriterion but it will not be a valid codeword with a modified decodingcriterion. In this construction XOR is used to correct stuck patterns.

In this example, it can be seen that every pair of constituent codewordsshare a common block of data bits with each other. In other words, thesame block of data is contained in two codewords. For instance, datablock D1 is in both CW1 and CW2, and therefore, CW1 and CW2 share datablock D1. Similarly, CW1 and CW3 share data block D2, CW1 and CW4 sharedata block D3, and CW1 and CW4 share data block D4. Further, CW2 and CW3share data block D5, CW3 and CW4 share data block D8, and CW4 and CW5share the XOR data block, etc.

In FIG. 2C, the intersection of two failing codewords is corrected usingXOR parity. In this example, the correction capability for constituentcodes is assumed to be equal to 1. The stuck pattern shown in FIG. 2Dcan also be corrected through XOR parity by making correction in parityblocks. The decoding fails when there are three or more codewordsfailing (see FIG. 2E). The stuck pattern shown in FIG. 2E can becorrected in the following manner. First, the XOR parity is constructedthrough decoded data as shown in FIG. 2F and compared with XOR paritystored in the data. In this example, calculated XOR parity and storedXOR parity differ at one location which indicates that this is thepossible error location (See FIG. 2G). The intersection of all pairs offailed codewords can contain the error at the estimated location. Atfailed error intersections, the flipping of the estimated bits can betried and regular decoding can be performed. In this example, flippingin the intersection of CW2 and CW3 will not lead to successful decoding.However, flipping the bit in the intersection of CW2 and CW4 will decodeall codewords successfully. In general, the value of I will be muchlarger than 3, and decoding through XOR parity can provide possibleerror locations better with large values of I and significantly reducethe number of flips for successful decoding. Let m error locations beprovided through XOR parity and there are FI possible error locationintersections. Then, 2 m bit flips can be tried on those FIintersections to get the successfully decoded data. In general, the XORparity can also be used to correct errors for the case where there aremore than 3 row codewords failing.

FIG. 2H is a simplified block diagram illustrating another generalizedproduct code (GPC) in accordance with certain embodiments of the presentdisclosure. Similar to the example of FIG. 2A, data is arranged in anarray such that each data chunk or block is protected twice byconstituent codes. Each codeword includes multiple data blocks andparity bits. Data blocks can include information blocks (or block ofinformation bits) and XOR blocks or XOR parity blocks, which are blocksformed by an XOR operation of information bits. There is parity onparity (POP) code constructed for constituent code parities. Unlike theGPC in FIG. 2A, which has only one XOR block, the GPC in FIG. 2H hasXOR-E and XOR-O, which are parities calculated on all even and odd datachunks respectively and are also protected twice using constituentcodes. In FIG. 2H, user data, or information bits, is organized as anarray of blocks of length I bits each labeled as D1, D2, . . . , D8.Padded zero-bits are shown in black. XOR parity intersections arelabeled as XOR-O and XOR-E. Parity bits and IC bits for componentcodewords and POP codewords are shown [2].

In the GPC example described above, the constituent codes arerepresented by BCH codes. However, other coding schemes can also beused. FIG. 3A is a simplified block diagram illustrating an example of aBose-Chaudhuri-Hocquenghem (BCH) decoder 300 in accordance with certainembodiments of the present disclosure. As illustrated in FIG. 3A, thedecoder receives a BCH codeword and starts an iterative decodingprocess. For each iteration, the BCH decoder performs syndromecalculation (step 310) on the received codeword, determines errorlocator polynomial (step 320), and performs Chien search or similarprocedures to determine roots of error locator polynomial (step 330).Roots of the error locator polynomial provide an indication of where theerrors in the codeword are located. The error locations are used forerror correction.

After correcting the errors, at 340, the decoder checks if the decodingprocess has resulted in a correct codeword. If so, the decoder outputsthe decoded bits. Otherwise, the decoder may generate a bit flippingpattern, flipping one or more bits of the codeword based on the patternand calculate syndrome values of the new codeword. The decoding processmay continue until a correct codeword is found and/or a predeterminedmaximum number of iterations is reached.

Given the natural numbers m and t, a t-error correcting binary BCH codeof length n=2^(m)−1 may be defined as:

c(x)εGF(2)[x]: deg c(x)≦n−1,c(α)=c(α²)=c(α³)= . . . =c(α^(2t))=0

where αεGF(2^(m)) is a primitive element. In other words, it is the setof all binary polynomials of degree at most n−1 such that when these aretreated as polynomials over GF(2^(m)), they must have α, α², α³, . . . ,α^(2t) as their roots.

If c(x) is the transmitted codeword, e(x) is the error polynomial, andR(x)=c(x)+e(x) is the received codeword, then given that α, α², α³, . .. , α^(2t) are roots of c(x), an initial component syndrome may becalculated as:

S _(i) =r(α^(i+1))=e(α^(i+1))

-   -   for i=0, 1, . . . , 2t−1.

The error locator polynomial generator uses the syndromes S₀, S₁,S_(2t−1) to generate the error location polynomial A(x), which isdefined as:

Λ(x)=Π_(i=1) ^(v)(1−α^(ji) x).

Several methods exist in the art for finding the locator polynomial—forexample, Berlekamp-Massey algorithm, Peterson's algorithm, and the like.The roots of the error location polynomial (i.e., j₀, j₁, j_(v) in theequation above) indicate the locations of the errors, so finding theroots of the error location polynomial corresponds to finding thelocations of the errors in a corresponding codeword.

Roots of the error location polynomial can be found using Chien search.For binary symbols, once the error locations have been identified,correction simply involves flipping the bit at each identified errorlocation. For non-binary symbols, the error magnitude needs to becalculated, for example, using Forney Algorithm, to find out themagnitude of the correction to be made.

In general, a decoder for product codes may perform BCH decoding on oneor more of the row constituent codes and/or column constituent codesiteratively to generate a correct codeword. For GPC, a decoder mayperform BCH decoding on one or more of the row constituent codesiteratively to generate a correct codeword.

FIG. 3B a block diagram illustrating a decoder according to anembodiment. As illustrated, the decoder has a control logic 310, aninitial syndrome generator 320, one or more syndrome buffers 331, one ormore page memories 340, and decoder 350. The initial syndrome generatoris used to generate initial values for the syndromes. For example, afterreceiving a new codeword, the initial syndrome generator generates oneor more syndromes for the decoder and stores them in the syndromebuffers 330. During the decoding procedure, the decoder utilizes thestored syndrome values to decode the codewords and correct errors.

In one embodiment, after finding an error pattern, the decoder correctsthe data stored in the memories 340 and also updates the correspondingsyndrome values stored in the syndrome buffers 330.

Decoder 350 includes Key equation solver (KES) 351, Chien search 352,and syndrome updater 353. In one embodiment, the syndrome values arecalculated by initial syndrome generator 320 to initialize syndromebuffer 330. The decoder reads syndrome values from buffers duringdecoding iterations. After processing key equation solver (KES) 351 andChien search 352, the decoder accesses page memory 340 and corrects thedata based on the determined error patterns. Some or all of syndromevalues are then updated in the syndrome buffer 330.

In one embodiment, the key equation solver is used to carry out theerror location polynomial σ(x), which may be defined as follows:

σ(x)=(1+xβ ₁)(1+xβ ₂) . . . (1+xβ _(v))=1+σ₁ x ¹+σ₂ x ²+σ₃ x ³ . . .+σ_(v) x ^(v).

The key equation describing the relation between S(x) and σ(x) may bederived as follows:

Ω(x)=S(x)×σ(x)mod x ^(2t)

where Ω(x) is the error evaluator polynomial, S(x) represents thesyndrome polynomial, and t represents the error correction capability ofthe code. Two of the popular methods for solving the key equation areBerlekamp-Massey and modified Euclidean algorithms. After the keyequation solver, Chien search is applied to find the roots of the errorlocation polynomial σ(x).

FIG. 4 is a simplified block diagram illustrating two pipelined decodersdecoding six codewords in parallel in accordance with certainembodiments of the present disclosure. It can be seen that two pipelineddecoders 410 and 420 decode six codewords, Data 1 to Data 6, inparallel. During time T1, Data 1 is processed in Syndrome Initializationin decoder 410, and Data 2 is processed in Syndrome Initialization indecoder 420. During time T2, Data 1 is processed in Key Equation Solverand Chien Search, and Data 3 is processed in Syndrome Initialization indecoder 410. Simultaneously, during time T2, Data 2 is processed in KeyEquation Solver and Chien Search, and Data 4 is processed in SyndromeInitialization in decoder 420. At a given time, six codewords could beprocessed in parallel. As explained above, in the GPC example, any twocodewords share many data bits. In other embodiments of GPC, twocodewords being processed in parallel can have a certain number of databits or a block of data bits in common. The parallel decoding of twocodewords at the same time can lead to clashes when both decoders updatesyndromes according to errors located in the intersection of the twodecoded codewords. These clashes will occur more frequently when thenumber of parallel decoders is increased. This problem can also occur inparallel decoding in a single decoder with pipelined structure oroperation.

In embodiments of the present disclosure, a coarse/fine decodingarchitecture is provided to avoid these clashes as described in detailbelow. It is noted that, as used herein, coarse decoding and finedecoding are also referred to as parallel decoding and sequentialdecoding, respectively.

Coarse Decoding Phase

In the coarse decoding phase constituent codewords are scheduled fordecoding on both decoders (dec-1 and dec-2, shown in FIG. 4 as 410 and420) in parallel. With three pipeline stages for every decoder, oneconstituent codeword decoding can potentially correct errors in theintersections with the next five scheduled codewords. Any correctionsmade in the intersections with the next five scheduled codewords willmake the decoding of the corresponding codewords void. For example,dec-1 decodes constituent codeword cw-1. It updates syndromes to correcterrors in the intersection, i.e., shared common block of bits, of cw-1and constituent codeword cw-2, as well as the intersection of the cw-1and constituent codeword cw-3. Then, any updates by decoders decodingcw-2 and cw-3 will be ignored or prohibited.

Fine Decoding Phase

The coarse decoding phase may cause a deadlock such that the decoding ofsome codewords gets ignored for many iterations of decoding. To avoidthis situation, the decoding architecture also provides a fine decodingphase after some number of iterations with the coarse decoding phase. Inthis phase, a single decoder without a pipeline structure is used fordecoding constituent codewords after coarse decoding. This singledecoder will be run slower, but, in most cases, very few constituentcodewords are left un-decoded after an iteration of fine decoding iscompleted.

Certain embodiments of the disclosure provide an error correctionapparatus configured for decoding a plurality of constituent codewordsin parallel. In some embodiments, the error correction apparatusincludes a memory and a processor coupled to the memory. The processoris configured to obtain a first message having a plurality ofconstituent codewords from the memory. The plurality of constituentcodewords are derived from a message encoded in a product code in whicheach constituent codeword has multiple blocks of data bits, and everypair of constituent codewords share a common block of data bits witheach other, wherein each constituent codeword corresponds to a class oferror correcting codes capable of correcting a pre-determined number oferrors.

FIG. 5 is a simplified block diagram illustrating a memory device, suchas a flash storage, according to an embodiment of the presentdisclosure. As shown in FIG. 5, memory device 500 includes a processor510, a memory array 520 coupled to the processor, and a decodingapparatus 530. The decoding apparatus is configured to perform coarsedecoding and fine decoding. In coarse decoding, the decoder decodes inparallel two or more codewords, which share a common block of bits, todetermine error information. Next, the decoder corrects errors in afirst codeword based on the error information. Here, the errors can becorrected at this point, or the errors can be marked for correction.Then, it is determined if the shared common block of data bits iscorrected. If the shared common data block is updated, then errorcorrection based on the error information is prohibited in codewordssharing the common block of data bits with the first codeword. In finedecoding, a single codeword is decoded at a time for error correction.

FIG. 5 can also represent a data decoding apparatus configured fordecoding a plurality of codewords in parallel. As shown in FIG. 5,decoding apparatus 500 includes processor 510, a memory 520 coupled tothe processor, and one or more decoders 530. Processor 510 is configuredto read encoded data including a plurality of codewords. The pluralityof codewords are encoded in a product code in which each codeword hasmultiple blocks of data bits and every two codewords share a commonblock with each other. Examples of the product code are described abovein connection with FIGS. 2A-2G. The one or more decoders 530 areconfigured to perform parallel decoding of two or more codewords.Decoder 530 can include one or more decoders capable of pipelineoperations for parallel decoding, such as decoders 410 and 420 in FIG.4. The decoders can also perform sequential decoding by deactivating thepipeline operation. Decoding apparatus 500 is configured to performcoarse decoding and fine decoding, which is described below withreference to FIG. 6.

FIG. 6 is a simplified flow chart 600 illustrating the operation ofdecoding apparatus 500 according to an embodiment of the presentdisclosure. The operation includes the following processes. In process610, the apparatus performs parallel decoding of two or more codewordsthat share a common data block to determine error information. Inprocess 620, the apparatus updates the first codeword if the errorinformation indicates that an error exists. In process 630, it isdetermined if the common data block between the first and secondcodewords is updated. In process 640, the decoding apparatus updates thesecond codeword based on the error information, unless the common blockis updated in the decoding of the first codeword. The coarse decoding isrepeated until the plurality of codewords are successfully decoded oruntil a predetermined number of iterations has been reached, as shown inprocesses 651 and 652. Next, in process 660, if a coarse decoding is notsuccessfully completed or a predetermined number of iterations has beenreached, then the fine decoding is performed. As shown in process 660,in the fine decoding, the codewords are decoded sequentially one at atime.

In coarse decoding, the parallel decoding can be performed by a singledecoder with a pipeline structure. Alternatively, the coarse decodingcan be performed by two or more decoders. In an embodiment, the finedecoding is performed by a single decoder with no pipeline operation. Insome embodiments, each decoder is configured to solve an error locationpolynomial using a key equation solver. Each decoder can be configuredto generate error information using Chien search. In some embodiments,each of the decoders can be configured for pipelined parallel decodingin three stages including syndrome initialization, key equation solverand Chien search, and syndrome update.

An example of the product code is the generalized product code (GPC)described above. In an embodiment, the encoded data or encoded messageincludes a group of data bits arranged in data blocks. The data blocksinclude blocks of information bits and one or more blocks of XOR bits.The XOR bits are formed by exclusive OR operation on the informationbits. Each codeword includes a number of data blocks and parity bits,and the parity bits are formed by encoding the data blocks using anerror-correcting coding scheme, e.g., BCH codes. The encoded datafurther includes parity-on-parity (POP) bits, which are formed byencoding the parity bits of the codewords using a seconderror-correcting coding scheme. The second error-correcting codingscheme can be the same as the first error-correcting coding scheme, or adifferent coding scheme. In this product code, each data block isincluded in two or more codewords, and every pair of codewords shares acommon data block. For this product code, the coarse decoding and finedecoding are described below in more detail with reference to FIGS. 7and 8.

FIG. 7 is a simplified flow chart illustrating a coarse decodingoperation 700 according to an embodiment of the present disclosure. Forthis product code, the apparatus is configured to decode the pluralityof codewords in parallel. In process 710, the initial syndromecalculation is performed. If this operation converges and no errors arefound, then the decoding is successful. Otherwise, main decoding, whichrefers to decoding of the codewords, is performed as shown in process720. Here, in each parallel decoding operation, two or more codewordsare decoded in parallel, and a codeword is updated to correct errorsunless a shared common data block is already updated or designated forupdate in this parallel decoding operation. If the plurality ofcodewords are not decoded successfully, then, at process 730, the paritybits and the POP bits are decoded and updated. In some embodiments, POPdecoding is performed sequentially. This coarse decoding operationrepeats the above decoding operations until all codewords are decodedsuccessfully, 790, or until a preset number of iterations is reached. InFIG. 7, process 740, Main & POP Stuck Check, determines if the decodingis successful, and process 750, Coarse Iteration Check, determines if apreset number of iterations is reached. If the coarse decoding is notsuccessful, then fine decoding is performed, which is described belowwith reference to FIG. 8.

FIG. 8 is a simplified flow chart illustrating a fine decoding operation800 according to an embodiment of the present disclosure. In the finedecoding, the apparatus is configured to decode the plurality ofcodewords sequentially, one at a time, and the codeword is updated tocorrect errors. If the plurality of codewords are not decodedsuccessfully, then the parity bits and the POP bits are decoded andupdated. The decoding processes involved in fine decoding are similar tothose in coarse decoding of FIG. 7, but are performed sequentially infine decoding.

In process 820, Modified Main Decoding With Updating, the codewords aredecoded sequentially, using a single decoder without a pipeline, and acodeword is updated to correct errors. If the plurality of codewords arenot decoded successfully, then, in process 830, the parity bits and thePOP bits are decoded and updated. This decoding operation repeats theabove decoding operations until all codewords are decoded successfully,890, or until a preset number of iterations is reached. In FIG. 8,process 840, Main & POP Stuck Check, determines if the decoding issuccessful, and process 850, Coarse Iteration Check, determines a presetnumber of iterations is reached. When fine decoding fails, in process860, an XOR SIR operation can be performed, in which informationprovided by the XOR bits is used for stuck intersection recovery (SIR).An example of error location estimation through XOR parity and possibleerror intersection is described above in connection with FIGS. 2A-2G. Ifthe SIR operation is successful, then the fine decoding is repeated. Ifthis process fails, then the decoding operation is determined to havefailed, at process 899.

To evaluate the performance, we have simulated this proposed coarse/finedecoding architecture for different code rates and at different codewordfailure rates (CFR). The results are shown in Tables 1-5 below. Forcomparison, we have assumed that there exists a hypothetical idealdecoder architecture, which is referred to as a Genie architecture, thatruns a single BCH decoder with a single pipeline that can run at 6 timeshigher clock cycle. The Genie architecture provides the best throughput;however, it should be noted that this Genie architecture is notpractical and is only used for comparison purposes.

In Table 1 and Table 2, throughput and latency are compared for theproposed architecture at the highest code rate (1280B/16 KB) at CFR1e-10 and 1e-6, respectively. Table 3 and Table 4 show throughput andlatency for the proposed architecture at the lowest code rate (2048B/16KB) at (CFR) 1e-10 and 1e-6, respectively.

TABLE 1 Throughput/latency for the proposed scheme at the highest coderate (1280 B/16 KB) at CFR 1e−10. Genie Proposed ArchitectureArchitecture Average Num. of Pipeline Stages 59.00 59.02 Throughput @300 MHz 1019 MB/s 1019 MB/s Avg. Latency @ 300 MHz 8.66 us 8.66 us

TABLE 2 Throughput/latency for the proposed scheme at the highest coderate (1280 B/16 KB) at CFR 1e−6. Genie Proposed ArchitectureArchitecture Average Num. of Pipeline Stages 59.24 60.6 Throughput @ 300MHz 1019 MB/s 1019 MB/s Avg. Latency @ 300 MHz 8.66 us 8.66 us

TABLE 3 Throughput/latency for the proposed scheme at the lowest coderate (2048 B/16 KB) at CFR 1e−10. Genie Proposed ArchitectureArchitecture Average Num. of Pipeline Stages 67.55 78.51 Throughput @300 MHz 1016 MB/s 875 MB/s Avg. Latency @ 300 MHz 9.06 us 10.52 us

TABLE 4 Throughput/latency for the proposed scheme at the lowest coderate (2048 B/16 KB) at CFR 1e−6. Genie Proposed ArchitectureArchitecture Average Num. of Pipeline Stages 81.18 95.31 Throughput 843MB/s 720 MB/s Avg. Latency 10.93 us 12.79 us

TABLE 5 Throughput loss due to the proposed architecture at lowest andhighest code rates compared to Genie architecture. Code Rate CFRThroughput Loss 1280 B/16 KB 1e−10    0% 1e−6    0% 2048 B/16 KB 1e−10~16% 1e−6 ~17%

It can be seen that there is no throughput loss by the GPC architectureat the highest code rate, and, at the lowest rate, it has been observedthat there has been small throughput loss from the proposed scheme.

The embodiments described above can support decoding several constituentdecoders in parallel for increasing throughput. The data dependencyissue described above is mitigated with two-phase operations—a coarsedecoding phase followed by a fine decoding. As noted above, coarsedecoding and fine decoding are also referred to as parallel decoding andsequential decoding, respectively. In the coarse decoding phase, severalconstituent decoders are decoded in parallel for throughput enhancement.However, one constituent codeword decoding can potentially correcterrors in the intersections with the next few scheduled codewords. Adeadlock condition might occur within coarse decoding; therefore, a finedecoding phase is used after coarse decoding, which applies a singleconstituent decoder without pipeline structure.

The coarse decoding, also referred to as parallel decoding, describedabove can be implemented according to the method described below. In anembodiment, the method includes reading, from a memory, encoded dataincluding a plurality of codewords. Each codeword has multiple datablocks, and each data block includes a number of data bits. The methodincludes decoding, in parallel, first and second codewords that share acommon data block to determine error information associated with eachcodeword. For each error detected in the decoding process, the errorinformation identifies one or more data blocks having errors andassociated error bit patterns. And the method includes updating thecodewords based on the error information associated with the common datablock.

The error information can be maintained in a data storage area in thesystem. In a specific embodiment, the storage area can include a datadependency list, which allows status of common data blocks in theintersection of multiple codewords being decoded in parallel. The methodcan be explained using a decoding apparatus with a two-bit errorcorrecting capability used to decode three codewords in parallel, CW1,CW2, and CW3. Using the example illustrated in FIG. 2B, each of thesecodewords includes four data blocks as listed below.

CW1 D1 D2 D3 D4 CW2 D1 D5 D6 D7 CW3 D2 D5 D8 D9Assuming the parallel decoding is carried out in a pipelined decoder,the data dependency list can be implemented using a FIFO (first-infirst-out) buffer that identifies the data blocks (error index) thathave been identified as having errors during the decoding process. Thedecoding skips the update of a common data block, if the common datablock is already updated in the decoding of an earlier step in theparallel decoding operation.

In the beginning of the decoding process, the data dependency list isempty, as indicated by the word “null.”

Data dependency list: {null, null, null, null}

Assuming the decoding of CW1 (D1, D2, D3, D4) finds errors in D2 and D3,the data dependency list is updated to appear as follows.

Data dependency list: {D2, D3, null, null}

The error correction stage of the decoder can be used to correct errorsin D2 and D3.

Next, the decoding of CW2 (D1, D5, D6, D7) finds errors in D5 and D6,which are not listed in the data dependency list. Therefore, the errorcorrection stage of the decoder can be used to correct errors in D5 andD6. And the data dependency list is updated to appear as follows.

Data dependency list: {D5, D6, D2, D3}

Next the decoding of CW3 (D2, D5, D8, D9) finds errors in D2 and D9.Since D2 is in the current data dependency, D2 will be or has beenupdated in the error correction stage of CW1. Therefore, the decodingskips the updating of D2 during the decoding of CW3. The errorcorrection stage of the decoder can be used to correct error in D9. Thedata dependency list is updated to appear as follows.

Data dependency list: {null, D9, D5, D6}

In this case, D2 does not appear in the data dependency list, because itis understood that the two codewords that share D2, namely D1 and D3,have already been processes, and D2 will not appear in another codeword.

At this point, CW1 has already exited the 3-stage pipelined decoder, anda fourth codeword CW4 enters the pipeline, with the data dependency listshowing the error indexes as {null, D9, D5, D6}.

It can be seen that the data dependency list identifies the data blockshaving errors (error indexes) in the two codewords that have beendecoded ahead of the third codeword in the 3-stage pipelined paralleldecoder. Since the decoder is assumed to have a two-bit error correctingcapability, two indexes are listed for each codeword. The methoddescribed above can also be applied to parallel decoding carried out bythree separate decoders instead of a 3-stage pipeline parallel decode.

In some embodiments, the data dependency list includes error bitpatterns for each of the identified error data blocks. For example,assuming each of the data blocks, D1, D2, . . . , has three data bits,then the possible error bit patterns include [001], [010], [100], . . ., etc. Each “1” bit in the error bit pattern indicates that thecorresponding bit in the data block is an error bit and needs to becorrected or flipped. For example, error bit pattern [010] indicatesthat the error is at the second bit, which is to be flipped in the errorcorrection step or error update step. For example, a data dependencylist of {D5, [010]; D6, [001]; D2 [100], D3, [010]} indicates that, inthe first codeword CW1, data blocks D2 and D3 have errors, and the errorin data block D2 is at the first bit ([100]) and the error in data blockD3 is at the second bit ([010]). Further, in the second codeword CW2,data blocks D5 and D6 have errors, and the error in data block D5 is atthe second bit ([010]) and the error in data block D6 is at the thirdbit ([001]). A more general data dependency list would include thefollowing error information.

-   -   CW1 error Index #1, CW1 error pattern #1;    -   CW1 error index #2, CW1 error pattern #2;    -   CW2 error Index #1, CW2 error pattern #1;    -   CW2 error index #2, CW2 error pattern #2.

The error information described above can be used in parallel decodingof codewords that may share a common data block. The method can includereading, from a memory, encoded data including a plurality of codewords.Each codeword has multiple data blocks, and each data block includes anumber of data bits. The method also includes decoding, in parallel,first and second codewords that share a common data block to determineerror information associated with each codeword. For each error, theerror information identifies one or more data blocks have errors andassociated error bit patterns. The method also includes updating thecodewords based on the error information associated with the common datablock.

FIG. 9 is a simplified flow chart illustrating a method 900 for paralleldecoding in accordance with certain embodiments of the presentdisclosure. This method can be applied to any parallel decoding ofconstituent codewords that share at least one common data block, such asthe parallel decoding of two constituent codewords from a GPC codewordor the parallel decoding of a row codeword and a column codeword from aTPC codeword. As described in connection with FIGS. 3A, 3B, 4, and 5,the decoding process in method 900 can include syndrome calculation(910), use key equation solver to compute error location polynomialaccording to syndrome values (920), and use Chien search to generateerror information, including error_indexes and error_patterns (930). Asdescribed above, the error_indexes identify the data block havingerrors, and the error_patterns, also referred to as error bit patterns,identify the error bit locations in a data block. The error indexes anderror_patterns are kept in the data dependency list.

Next, updating the codewords is based on the error informationassociated with the common data block. At step 940, the method includesdetermining if the error index for the codeword being decoded alreadyexists in the data dependency list. If not, the error index for thecodeword being decoded does not exist in the data dependency list, andthere is no risk that a common data block will be updated twice in thedecoding of two codewords. Therefore, the method proceeds to update thecurrent codeword, i.e., to correct errors in all data blocks in thecurrent codeword (960). At 970, the data dependency list is updated witherror information generated by Chien search. At this point, the decodingof the current codeword is finished (990).

If, however, at step 940, the data block identified by the error_indexis a common data block that has already been identified as having anerror in another codeword being decoded in the parallel decodingprocess, the data block will be updated in the correction step of thatcodeword. As a result, the updating of all data blocks in the currentcodeword is skipped to prevent updating the common data block twice(950). Next, at 980, the data dependency list is updated with “null” inthe entries for the current codeword, since no error is corrected in thecurrent codeword. At this point, the decoding of the current codeword isfinished (990).

In the method illustrated by the flow chart in FIG. 9, if a common blockis already being updated by the decoding of another codeword accordingto the error_index in the data dependency list, then the currentcodeword is not updated, and will need to be updated in anotheriteration of decoding. In some other embodiments, both the error_indexand the error_pattern are used in the parallel decoding process, asillustrated in FIG. 10.

FIG. 10 is a simplified flow chart illustrating another method forparallel decoding in accordance with alternative embodiments of thepresent disclosure. Similar to method 900 in FIG. 9, in method 1000 inFIG. 10, the decoding process can include syndrome calculation (1010),use the key equation solver to compute an error location polynomialaccording to syndrome values (1020), and use Chien search to generateerror information, including error_indexes and error_patterns (1030). Asdescribed above, the error_indexes identify the data block havingerrors, and the error_patterns, also referred to as error bit patterns,identify the error bit locations in a data block. The error indexes anderror_patterns are kept in the data dependency list.

Next, the decision to update the codeword is based on the errorinformation associated with the common data block. At step 1040, themethod includes determining if the error index for the codeword beingdecoded already exists in the data dependency list. If not, theerror_index for the codeword being decoded does not exist in the datadependency list, and there is no risk that a common data block will beupdated twice in the decoding of two codewords. Therefore, the methodproceeds to update the current codeword, i.e., to correct errors in alldata blocks in the current codeword. At 1070, the data dependency listis updated with error information generated by Chien search. Steps 1074an 1076 guide the decoding through the list of identified errors. Afterall the errors in the codeword are updated, the decoding of the currentcodeword is finished (1090).

If, however, at step 1040, the data block identified by the error_indexis a common data block that has already been identified as having anerror in another codeword being decoded in the parallel decodingprocess, the data block will be updated in the correction step of thatcodeword. A further test is carried out (1042) to determine if theidentified error bit pattern (error_pattern) is the same as theerror_pattern for the data block identified by the error-index in thedata dependent list. If the error pattern is the same, it indicates thatthe error in this data block has been corrected in an earlier decoding.Therefore, the data block can be considered having been updated (orcorrected), and there is no need to update it again. Therefore, thedecoder skips the update of this error pattern (1062). Next, at 1072,the data dependency list is updated with “null” in the entries for thecurrent codeword, since no error is corrected in the current codeword.At this point, steps 1074 an 1076 guide the decoding through the list ofidentified errors. After all the errors in the codeword are updated, thedecoding of the current codeword is finished (1090).

If, at step 1042, it is determined that the identified error bit pattern(error_pattern) is not the same as the error_pattern for the data blockidentified by the error-index in the data dependent list, the data blockidentified by the error_index is a common data block that has alreadybeen identified as having a different error in another codeword beingdecoded in the parallel decoding process. As a result, the updating ofall data blocks in the current codeword is skipped to prevent updatingthe common data block twice (1050). Next, at 1080, the data dependencylist is updated with “null” in the entries for the current codeword,since no error is corrected in the current codeword. At this point, thedecoding of the current codeword is finished (1090).

Compared with method 900 in FIG. 9, method 1000 in FIG. 10 uses botherror index and error pattern information in the data dependency list.Method 1000 can help to reduce the number of skip procedures to beapplied, and it can reduce the number of codewords that include datablocks which have errors but have not been updated. As a result, thelatency loss can be shortened, and the decoding throughput can beincreased.

Method 1000 described above can be implemented using the decodingapparatus described above in connection with FIGS. 3A, 3B, 4, and 5. Forexample, a decoding apparatus configured for decoding a plurality ofcodewords in parallel can include a memory, a processor coupled to thememory, and one or more decoders configured to perform parallel decodingof two codewords. The processor is configured to read encoded dataincluding a plurality of codewords from the memory. The plurality ofcodewords is encoded in a product code in which each codeword hasmultiple data blocks, and each data block has a number of data bits.

In some embodiments, the apparatus is configured to perform paralleldecoding of first and second codewords sharing a common data block todetermine error information associated with each codeword. For everyerror, the error information identifies one or more data blocks havingerrors and associated error bit patterns. The apparatus is configured toupdate the first codeword if the error information associated with thefirst codeword indicates an error and, if the error informationassociated with the second codeword indicates an error, determinewhether to update the second codeword as follows. First, the decodingapparatus determines if the common data block between the first andsecond codewords is updated in the updating of the first codeword. Ifthe common data block is not updated, the decoding apparatus updates thesecond codeword based on the error information associated with thesecond codeword. If the common data block is updated and the error bitpattern in the common data block identified in the decoding of thesecond codeword is the same as the error bit pattern in the common datablock identified in the decoding of the first codeword, the decodingapparatus updates data blocks other than the common data block in thesecond codeword without updating the common data block. Further, if thecommon data block is updated and the error bit pattern in the commondata block identified in the decoding of the second codeword isdifferent from the error bit pattern in the common data block identifiedin the decoding of the first codeword, the decoding apparatus skips theupdating of the second codeword. In the latter case, the error in thesecond codeword is not updated, and it will be processed in the nextdecoding step.

In some embodiments, a memory device can include the decoding mechanismsdescribed above. For example, the memory device can include a memoryarray, a processor coupled to the memory array, and a decodingapparatus. The decoding apparatus is configured to perform paralleldecoding of codewords. Each of the codewords has a plurality of datablocks, and each data block having a number of data bits. The decodingapparatus is configured to decode in parallel two or more codewords,which share a common data block, to determine error informationassociated with each codeword. For each error, the error informationidentifies one or more data blocks having errors and associated errorbit patterns. The decoding apparatus is configured to update the two ormore codewords based on the identified one or more data blocks havingerrors and the associated error bit patterns.

In an embodiment of the above memory device, the decoding apparatus isconfigured to update a first codeword according to error informationassociated with the first codeword. The decoding apparatus is alsoconfigured to update a second codeword according to the errorinformation associated with the second codeword, unless the common datablock is updated in the updating of the first codeword and the error bitpattern in the common data block identified in the decoding of thesecond codeword is different from the error bit pattern in the commondata block identified in the decoding of the first codeword.

In some embodiments of the memory device, the decoding apparatus isconfigured to decode a plurality of codewords that are encoded in aproduct code in which each codeword has multiple blocks of data bits,wherein codewords belonging to a same pair of codewords share a commondata block.

The embodiments disclosed herein are not to be limited in scope by thespecific embodiments described herein. Various modifications of theembodiments of the present disclosure, in addition to those describedherein, will be apparent to those of ordinary skill in the art from theforegoing description and accompanying drawings. Further, although someof the embodiments of the present disclosure have been described in thecontext of a particular implementation in a particular environment for aparticular purpose, those of ordinary skill in the art will recognizethat its usefulness is not limited thereto and that the embodiments ofthe present disclosure can be beneficially implemented in any number ofenvironments for any number of purposes.

FIG. 11 is a simplified block diagram illustrating an apparatus that maybe used to implement various embodiments according the presentdisclosure. FIG. 11 is merely illustrative of an embodimentincorporating the present disclosure and does not limit the scope of thedisclosure as recited in the claims. One of ordinary skill in the artwould recognize other variations, modifications, and alternatives. Inone embodiment, computer system 1100 typically includes a monitor 1110,a computer 1120, user output devices 1130, user input devices 1140,communications interface 1150, and the like.

As shown in FIG. 11, computer 1120 may include a processor(s) 1160 thatcommunicates with a number of peripheral devices via a bus subsystem1190. These peripheral devices may include user output devices 1130,user input devices 1140, communications interface 1150, and a storagesubsystem, such as random access memory (RAM) 1170 and disk drive 1180.

User input devices 1140 can include all possible types of devices andmechanisms for inputting information to computer system 1120. These mayinclude a keyboard, a keypad, a touch screen incorporated into thedisplay, audio input devices such as voice recognition systems,microphones, and other types of input devices. In various embodiments,user input devices 1140 are typically embodied as a computer mouse, atrackball, a track pad, a joystick, wireless remote, drawing tablet,voice command system, eye tracking system, and the like. User inputdevices 1140 typically allow a user to select objects, icons, text andthe like that appear on the monitor 1110 via a command such as a clickof a button or the like.

User output devices 1130 include all possible types of devices andmechanisms for outputting information from computer 1120. These mayinclude a display (e.g., monitor 1110), non-visual displays such asaudio output devices, etc.

Communications interface 1150 provides an interface to othercommunication networks and devices. Communications interface 1150 mayserve as an interface for receiving data from and transmitting data toother systems. Embodiments of communications interface 1150 typicallyinclude an Ethernet card, a modem (telephone, satellite, cable, ISDN),(asynchronous) digital subscriber line (DSL) unit, FireWire interface,USB interface, and the like. For example, communications interface 1150may be coupled to a computer network, to a FireWire bus, or the like. Inother embodiments, communications interfaces 1150 may be physicallyintegrated on the motherboard of computer 1120, and may be a softwareprogram, such as soft DSL, or the like.

In various embodiments, computer system 1100 may also include softwarethat enables communications over a network such as the HTTP, TCP/IP,RTP/RTSP protocols, and the like. In alternative embodiments of thepresent disclosure, other communications software and transfer protocolsmay also be used, for example IPX, UDP or the like. In some embodiments,computer 1120 includes one or more Xeon microprocessors from Intel asprocessor(s) 1160. Further, in one embodiment, computer 1120 includes aUNIX-based operating system.

RAM 1170 and disk drive 1180 are examples of tangible storage mediaconfigured to store data such as embodiments of the present disclosure,including executable computer code, human readable code, or the like.Other types of tangible storage media include floppy disks, removablehard disks, optical storage media such as CD-ROMS, DVDs and bar codes,semiconductor memories such as flash memories, read-only-memories(ROMS), battery-backed volatile memories, networked storage devices, andthe like. RAM 1170 and disk drive 1180 may be configured to store thebasic programming and data constructs that provide the functionality ofthe present disclosure.

Software code modules and instructions that provide the functionality ofthe present disclosure may be stored in RAM 1170 and disk drive 1180.These software modules may be executed by processor(s) 1160. RAM 1170and disk drive 1180 may also provide a repository for storing data usedin accordance with the present disclosure.

RAM 1170 and disk drive 1180 may include a number of memories includinga main random access memory (RAM) for storage of instructions and dataduring program execution and a read only memory (ROM) in which fixednon-transitory instructions are stored. RAM 1170 and disk drive 1180 mayinclude a file storage subsystem providing persistent (non-volatile)storage for program and data files. RAM 1170 and disk drive 1180 mayalso include removable storage systems, such as removable flash memory.

Bus subsystem 1190 provides a mechanism for letting the variouscomponents and subsystems of computer 1120 communicate with each otheras intended. Although bus subsystem 1190 is shown schematically as asingle bus, alternative embodiments of the bus subsystem may utilizemultiple busses.

FIG. 11 is representative of a computer system capable of embodying thepresent disclosure. It will be readily apparent to one of ordinary skillin the art that many other hardware and software configurations aresuitable for use with the present disclosure. For example, the computermay be a desktop, portable, rack-mounted or tablet configuration.Additionally, the computer may be a series of networked computers.Further, the use of other microprocessors are contemplated, such asPentium™ or Itanium™ microprocessors; Opteron™ or AthlonXP™microprocessors from Advanced Micro Devices, Inc.; and the like.Further, other types of operating systems are contemplated, such asWindows®, WindowsXP®, WindowsNT®, or the like from MicrosoftCorporation, Solaris from Sun Microsystems, LINUX, UNIX, and the like.In still other embodiments, the techniques described above may beimplemented upon a chip or an auxiliary processing board.

Various embodiments of the present disclosure can be implemented in theform of logic in software or hardware or a combination of both. Thelogic may be stored in a computer readable or machine-readablenon-transitory storage medium as a set of instructions adapted to directa processor of a computer system to perform a set of steps disclosed inembodiments of the present disclosure. The logic may form part of acomputer program product adapted to direct an information-processingdevice to perform a set of steps disclosed in embodiments of the presentdisclosure. Based on the disclosure and teachings provided herein, aperson of ordinary skill in the art will appreciate other ways and/ormethods to implement the present disclosure.

The data structures and code described herein may be partially or fullystored on a computer-readable storage medium and/or a hardware moduleand/or hardware apparatus. A computer-readable storage medium includes,but is not limited to, volatile memory, non-volatile memory, magneticand optical storage devices such as disk drives, magnetic tape, CDs(compact discs), DVDs (digital versatile discs or digital video discs),or other media, now known or later developed, that are capable ofstoring code and/or data. Hardware modules or apparatuses describedherein include, but are not limited to, application-specific integratedcircuits (ASICs), field-programmable gate arrays (FPGAs), dedicated orshared processors, and/or other hardware modules or apparatuses nowknown or later developed.

The methods and processes described herein may be partially or fullyembodied as code and/or data stored in a computer-readable storagemedium or device, so that when a computer system reads and executes thecode and/or data, the computer system performs the associated methodsand processes. The methods and processes may also be partially or fullyembodied in hardware modules or apparatuses, so that when the hardwaremodules or apparatuses are activated, they perform the associatedmethods and processes. The methods and processes disclosed herein may beembodied using a combination of code, data, and hardware modules orapparatuses.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, the disclosure is not limitedto the details provided. There are many alternative ways of implementingthe disclosure. The disclosed embodiments are illustrative and notrestrictive.

What is claimed is:
 1. A decoding apparatus configured for decoding aplurality of codewords in parallel, comprising: a memory; a processorcoupled to the memory, the processor configured to read encoded dataincluding a plurality of codewords from the memory, the plurality ofcodewords being encoded in a product code in which each codeword hasmultiple data blocks, each data block having a number of data bits; andone or more decoders, configured to perform parallel decoding of twocodewords, wherein the decoding of each codeword at least partiallyoverlaps in time with the decoding of the other codeword; wherein theapparatus is configured to: perform parallel decoding of a firstcodeword and a second codeword sharing a common data block to determineerror information associated with each codeword, wherein the errorinformation identifies one or more data blocks having one or more errorsand associated error bit patterns; update the first codeword based onthe error information indicating an error; if the error informationindicates an error in the decoding of the second codeword, determinewhether to update the second codeword as follows: determine if thecommon data block between the first codeword and the second codeword hasbeen identified as having an error in the decoding of the firstcodeword; upon determining that the common data block has not beenidentified as having an error, update the second codeword based on theerror information; upon determining that the common data block has beenidentified as having an error and that an error bit pattern in thecommon data block identified in the decoding of the second codeword isthe same as an error bit pattern in the common data block identifiedfrom the error information based on the decoding of the first codeword,update data blocks other than the common data block in the secondcodeword without updating the common data block; and upon determiningthat the common data block has been identified as having an error andthat the error bit pattern in the common data block identified in thedecoding of the second codeword is different from the error bit patternin the common data block identified from the error information based onthe decoding of the first codeword, skip the updating of the secondcodeword.
 2. The apparatus of claim 1, wherein the apparatus is furtherconfigured to perform sequential decoding, in which the codewords aredecoded sequentially, wherein the apparatus is configured to performsequential decoding only if it is determined that the parallel decodinghas failed to decode the plurality of codewords.
 3. The apparatus ofclaim 1, wherein the parallel decoding is repeated until the pluralityof codewords are successfully decoded or until a predetermined number ofiterations has been reached.
 4. The apparatus of claim 1, wherein theparallel decoding is performed by a single decoder with a pipelinestructure.
 5. The apparatus of claim 1, wherein the parallel decoding isperformed by two or more decoders.
 6. The apparatus of claim 1, whereinthe decoding apparatus is configured for decoding a plurality ofcodewords in parallel, wherein codewords belonging to a same pair ofcodewords share a common data block.
 7. The apparatus of claim 1,wherein: the encoded data comprises a group of data bits arranged indata blocks, the data blocks including blocks of information bits; eachcodeword including a number of data blocks and parity bits, the paritybits formed by encoding the data blocks using an error-correcting codingscheme; the encoded data further including parity-on-parity (POP) bits,which are formed by encoding the parity bits of the codewords using asecond error-correcting coding scheme; wherein each data block isincluded in two or more codewords, and wherein codewords belonging to asame pair of codewords share a common data block.
 8. The apparatus ofclaim 7, wherein the apparatus is configured to: decode the plurality ofcodewords, wherein, in each parallel decoding operation, two or morecodewords are decoded in parallel, and a codeword is updated to correcterrors unless a shared common data block is previously updated in saidparallel decoding operation; if the plurality of codewords are notdecoded successfully, decode and update the parity bits and the POPbits; and repeat the above parallel decoding operations until allcodewords are decoded successfully or until a preset number ofiterations is reached and the parallel decoding operation is determinedto be unsuccessful.
 9. The apparatus of claim 8, wherein, if theparallel decoding operation is determined to be unsuccessful, asequential decoding is performed, in which the apparatus is configuredto: decode the plurality of codewords, wherein each codeword is decodedsequentially and updated to correct errors; if the plurality ofcodewords are not decoded successfully, decode and update the paritybits and the POP bits; and repeat the above decoding operations untilall codewords are decoded successfully or until a preset number ofiterations is reached.
 10. A memory device, comprising: a memory array;a processor coupled to the memory array; and a decoding apparatusconfigured to perform parallel decoding of codewords, each of thecodewords having a plurality of data blocks, each data block having anumber of data bits; wherein the decoding apparatus is configured to:decode in parallel two or more codewords, which share at least a commondata block, to determine error information associated with eachcodeword, wherein, for each error, the error information identifies adata blocks having the error and associated error bit pattern; andupdate the two or more codewords based on the identified one or moredata blocks having errors and the associated error bit patterns.
 11. Thememory device of claim 10, wherein the decoding apparatus is configuredto: update a first codeword according to the error information; andupdate a second codeword according to the error information associatedwith the second codeword, unless the common data block is updated in theupdating of the first codeword and the error bit pattern in the commondata block identified in the decoding of the second codeword isdifferent from the error bit pattern in the common data block identifiedin the decoding of the first codeword.
 12. The memory device of claim10, wherein the decoding apparatus is configured to decode a pluralityof codewords that are encoded in a product code in which each codewordhas multiple blocks of data bits, wherein codewords belonging to a samepair of codewords share a common data block.
 13. The memory device ofclaim 10, wherein the decoding apparatus is configured to decode encodeddata, wherein: the encoded data includes codewords, each codeword havinga number of data blocks and parity bits, the parity bits being formed byencoding the data blocks using a first error-correcting coding scheme;the encoded data further includes parity-on-parity (POP) bits, which areformed by encoding the parity bits of the codewords using a seconderror-correcting coding scheme; and wherein each data block is includedin two or more codewords, and codewords belonging to a same pair ofcodewords share a common data block.
 14. The memory device of claim 13,wherein, in the parallel decoding, the apparatus is configured to:decode the plurality of codewords, and if the plurality of codewords arenot decoded successfully, decode and update the parity bits and the POPbits; and repeat the above decoding operations until all codewords aredecoded successfully or until a preset number of iterations is reachedand the parallel decoding is determined to be unsuccessful.
 15. Thememory device of claim 13, if the parallel decoding operation isdetermined to be unsuccessful, a sequential decoding is performed, inwhich the apparatus is configured to: decode the plurality of codewords,wherein each codeword is decoded sequentially, and the codeword isupdated to correct errors; if the plurality of codewords are not decodedsuccessfully, decode and update the parity bits and the POP bits; andrepeat the above decoding operations until all codewords are decodedsuccessfully or until a preset number of iterations is reached.
 16. Amethod for decoding data, the method comprising: reading, from a memory,encoded data including a plurality of codewords, each codeword havingmultiple data blocks, each data block including a number of data bits;decoding, in parallel, a first codeword and a second codeword that sharea common data block to determine error information associated with eachcodeword, wherein the decoding of the first codeword at least partiallyoverlaps in time with the decoding of the second codeword, and wherein,for each error, the error information identifies a data block having theerror and associated error bit pattern; and updating the codewords basedon the error information associated with the common data block.
 17. Themethod of claim 16, further comprising: updating the first codewordaccording to the error information associated with the first codeword;updating the second codeword according to the error informationassociated with the second codeword, unless the common data block isupdated in the updating of the first codeword and the error bit patternin the common data block identified in the decoding of the secondcodeword is different from the error bit pattern in the common datablock identified in the decoding of the first codeword.
 18. The methodof claim 16, wherein the decoding apparatus is configured to decodeencoded data, wherein: the encoded data includes codewords, eachcodeword having a number of data blocks and parity bits, the parity bitsbeing formed by encoding the data blocks using a first error-correctingcoding scheme; the encoded data further includes parity-on-parity (POP)bits, which are formed by encoding the parity bits of the codewordsusing a second error-correcting coding scheme; wherein each data blockis included in two or more codewords, and codewords belonging to a samepair of codewords share a common data block.
 19. The method of claim 18,further comprising: in parallel decoding, performing parallel decodingof the plurality of codewords; and if the parallel decoding isunsuccessful, performing sequential decoding in which the codewords aredecoded sequentially.
 20. The method of claim 19, further comprising, inthe parallel decoding: decoding the plurality of codewords; if theplurality of codewords are not decoded successfully, decoding andupdating the parity bits and the POP bits; and repeating the abovedecoding operations until all codewords are decoded successfully oruntil a preset number of iterations is reached.